There are multiple ways in which soil moisture can be determined: use of in-situ soil moisture sensors, through hydrological modeling and by using satellite observations. Well-known satellite missions which were specifically designed for soil moisture derivations are the Soil Moisture and Ocean Salinity (SMOS) satellite, which is part of ESA's Living Planet Program and NASA's Soil Moisture Active Passive (SMAP) mission. The raw microwave brightness temperature data as observed by these satellites as well as the derived soil moisture data are made available by both ESA and NASA. Multiple techniques have been developed to improve the spatial resolution of the temperature data and soil moisture data, e.g. by using disaggregation.
Disaggregation based on Physical And Theoretical scale Change (DisPATCh) is an algorithm dedicated to the disaggregation of soil moisture observations using high-resolution soil temperature data. As described in “Disaggregation of SMOS Soil Moisture in Southeasthern Australia” by O. Merlin, C. Rudiger, A. Al Bitar, P. Richaume, J. P. Walker, and Y. H. Kerr (IEEE Transactions on Geoscience and Remote Sensing Volume 50, Issue: 5, pages 1556-1571), DisPATCh converts soil temperature fields into soil moisture fields given a semi-empirical soil evaporative efficiency model and a first-order Taylor series expansion around the field-mean soil moisture. DisPATCh improves the resolution of lower resolution soil moisture data, e.g. of ESA's SMOS (Soil Moisture and Ocean Salinity) satellite, with the use of soil temperature data of, for example, MODIS (MODerate-resolution Imaging Spectroradiometer) VIS/IR data from one of the Terra or Aqua satellites. This results in soil moisture data with a resolution of 1 kmxl km.
A drawback of the DisPATCh algorithm is that the resolution is still relatively coarse at 1 km×1 km, in particular this is too coarse for local field applications.